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Diagonalization
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What is diagonalization?
Diagonalization is the process of finding a diagonal matrix that is similar to a given square matrix.
What is a diagonal matrix?
A diagonal matrix is a matrix where the elements outside the main diagonal are all zero.
How do you check if a matrix is diagonalizable?
A matrix is diagonalizable if there are enough linearly independent eigenvectors to form a basis for its column space.
What is an eigenvalue?
An eigenvalue is a scalar \( \lambda \) such that \( A \mathbf{v} = \lambda \mathbf{v} \) for some nonzero vector \( \mathbf{v} \) and square matrix A.
What is an eigenvector?
An eigenvector is a nonzero vector \( \mathbf{v} \) that, when multiplied by a matrix, results in a scalar multiple of itself, \( A \mathbf{v} = \lambda \mathbf{v} \).
What is the characteristic polynomial?
The characteristic polynomial of a matrix A is the polynomial given by the determinant \( \det(A - \lambda I) \), where I is the identity matrix and \( \lambda \) is a scalar.
What is a similar matrix?
Two matrices A and B are similar if there exists an invertible matrix P such that \( P^{-1}AP = B \).
What conditions must a matrix meet to be diagonalizable?
A matrix must have n linearly independent eigenvectors to be diagonalizable, where n is the size of the matrix.
How is the diagonal matrix related to the original matrix?
The diagonal matrix contains the eigenvalues of the original matrix along its main diagonal, in the same order as the corresponding eigenvectors in the columns of the matrix used to diagonalize.
What does the eigenspace of an eigenvalue represent?
The eigenspace of an eigenvalue is the set of all eigenvectors corresponding to that eigenvalue, along with the zero vector.
What is the geometric multiplicity of an eigenvalue?
The geometric multiplicity of an eigenvalue is the dimension of its eigenspace, or the number of linearly independent eigenvectors associated with that eigenvalue.
What is spectral theorem?
The spectral theorem states that a matrix is diagonalizable using an orthonormal basis of eigenvectors if and only if the matrix is normal (commutes with its conjugate transpose).
What is the algebraic multiplicity of an eigenvalue?
The algebraic multiplicity of an eigenvalue is the number of times the eigenvalue appears as a root of the characteristic polynomial.
What role does the determinant play in diagonalization?
The determinant can help in finding eigenvalues as it is used in the characteristic polynomial, which is solved to get eigenvalues.
What is the trace of a matrix and its relation with eigenvalues?
The trace of a matrix is the sum of its diagonal entries and is equal to the sum of its eigenvalues considering their algebraic multiplicities.
What is the effect of matrix diagonalization on matrix powers?
Matrix diagonalization simplifies the computation of matrix powers, as powering a diagonal matrix involves simply raising each diagonal element to the power.
Can a complex matrix be diagonalizable over the real numbers?
If a matrix has complex eigenvalues, it is not diagonalizable over the real numbers, but it can be diagonalized over the complex numbers.
How does diagonality relate to matrix exponentials?
The exponential of a diagonalizable matrix simplifies to the exponentials of the individual eigenvalues along the main diagonal of the diagonal matrix.
What is a defective matrix?
A defective matrix is a matrix that does not have enough linearly independent eigenvectors to be diagonalizable.
How does diagonalization affect system of differential equations?
Diagonalization can simplify the solution of a system of linear differential equations by decoupling the system into individual equations.
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